Bibliographic record
Abstract
Mike, Nancy. Elisapee and her Baby Seagull. Inhabit Media, 2017.In this picture book, Nancy Mike tells the story of an Inuit girl who raises a seagull from a chick to adulthood and finally returns it to the wild. Through caring for Nau, the seagull, Elisapee learns “how to care, how to feed an animal and how to have patience.” Finally she learns to let go as the grown-up Nau joins the other seagulls. Mike’s text is simple and age appropriate for the intended lower elementary audience.Charlene Chua’s pictures fill most of the book with colour. The text is overprinted on the backgrounds. Her artwork is cartoonish. The characters have oversized eyes and tiny noses, reminiscent of Mickey Mouse or some manga characters. However, her images do capture the natural world of the Arctic environment. Chua has included some fun visual jokes, such as a large gull trying to fit into a small box and a krill jumping from a boy’s hand when he’s trying to feed the gull.This book gently introduces some life lessons in an Inuit context. Highly recommended for public libraries and school libraries and for libraries that collect Inuit children’s literature.Highly recommended: 4 stars out of 4Reviewer: Sandy CampbellSandy is a Health Sciences Librarian at the University of Alberta, who has written hundreds of book reviews across many disciplines. Sandy thinks that sharing books with children is one of the greatest gifts anyone can give.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.169 | 0.097 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".